Assessing the E?ect of Real Spatial Resolution of InSitu UAV Multispectral Images on Seedling RapeseedGrowth Monitoring

Abstract: The spatial resolution of in situ unmanned aerial vehicle (UAV) multispectral imageshas a crucial e?ect on crop growth monitoring and image acquisition e?ciency. However, existingstudies about optimal spatial resolution for crop monitoring are mainly based on resampled images.Therefore, the resampled spatial resolution in these studies might not be applicable to in situUAV images. In order to obtain optimal spatial resolution of in situ UAV multispectral imagesfor crop growth monitoring, a RedEdge Micasense 3 camera was installed onto a DJI M600 UAV?ying at di?erent heights of 22, 29, 44, 88, and 176m to capture images of seedling rapeseed withground sampling distances (GSD) of 1.35, 1.69, 2.61, 5.73, and 11.61 cm, respectively. Meanwhile,the normalized di?erence vegetation index (NDVI) measured by a GreenSeeker (GS-NDVI) and leafarea index (LAI) were collected to evaluate the performance of nine vegetation indices (VIs) andVI*plant height (PH) at di?erent GSDs for rapeseed growth monitoring. The results showed that thenormalized di?erence red edge index (NDRE) had a better performance for estimating GS-NDVI(R2=0.812) and LAI (R2=0.717), compared with other VIs. Moreover, when GSD was less than2.61 cm, the NDRE*PH derived from in situ UAV images outperformed the NDRE for LAI estimation(R2=0.757). At oversized GSD (?5.73 cm), imprecise PH information and a large heterogeneity withinthe pixel (revealed by semi-variogram analysis) resulted in a large random error for LAI estimationby NDRE*PH. Furthermore, the image collection and processing time at 1.35 cm GSD was aboutthree times as long as that at 2.61 cm. The result of this study suggested that NDRE*PH from UAVmultispectral images with a spatial resolution around 2.61 cm could be a preferential selection forseedling rapeseed growth monitoring, while NDRE alone might have a better performance for lowspatial resolution images

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Authors: Jian Zhang, Chufeng Wang, Chenghai Yang, Tianjin Xie, Zhao Jiang, Tao Hu, Zhibang Luo, Guangsheng Zhou, Jing Xie

Associations: Macro Agriculture Research Institute, College of Resource and Environment, Huazhong Agricultural University; Key Laboratory of Farmland Conservation in the Middle and Lower Reaches of the Ministry of Agriculture, Wuhan, China; Aerial Application Technology Research Unit, USDA-Agricultural Research Service;
College of Plant Science and Technology, Huazhong Agricultural University; College of Science, Huazhong Agricultural University